Centos8 搭建 kafka2.8 .net5 简单使用kafka

1、选择要安装的版本http://kafka.apache.org/downloads

2、wget https://mirrors.bfsu.edu.cn/apache/kafka/2.8.0/kafka_2.12-2.8.0.tgz

3、tar -xzvf kafka_2.12-2.8.0.tgz

4、重要的文件夹 bin（所用sh文件都在这里） 和 config（所有配置文件都在这里）

5、修改zookeeper.properties和server.properties（这里有个重要的概念  kafka是依赖于zookeeper的）

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
# 
#    http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# the directory where the snapshot is stored.
dataDir=/tmp/zookeeper
# the port at which the clients will connect
clientPort=2181
# disable the per-ip limit on the number of connections since this is a non-production config
maxClientCnxns=0
# Disable the adminserver by default to avoid port conflicts.
# Set the port to something non-conflicting if choosing to enable this
admin.enableServer=false
# admin.serverPort=8080

 Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# see kafka.server.KafkaConfig for additional details and defaults

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0

############################# Socket Server Settings #############################
host.name=192.168.232.128
# The address the socket server listens on. It will get the value returned from 
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set, 
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
advertised.listeners=PLAINTEXT://192.168.232.128:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600


############################# Log Basics #############################

# A comma separated list of directories under which to store log files
log.dirs=/tmp/kafka-logs

# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1

# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
log.flush.interval.messages=10000

# The maximum amount of time a message can sit in a log before we force a flush
log.flush.interval.ms=3000

############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824

# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=localhost:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=18000


############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

192.168.232.128是我的虚拟机的ip
2181是zookeeper的端口  9092是kafka的端口

6、进入到解压的文件夹

7、启动zookeeper  bin/zookeeper-server-start.sh config/zookeeper.properties

8、启动kafka bin/kafka-server-start.sh config/server.properties

9、创建topic  bin/kafka-topics.sh --create --zookeeper 192.168.232.128:2181 --replication-factor 1 --partitions 1 --topic kafka-hello

10、开始测试

11、启动发布者进行消息写入 bin/kafka-console-producer.sh --broker-list 192.168.232.128:9092 --topic kafka-hello

12、启动订阅者进行消息读取 bin/kafka-console-consumer.sh --bootstrap-server 192.168.232.128:9092 --topic kafka-hello --from-beginning

13、一切顺利的话就算搭建完成

14、还差一步应该就完美了，设置一下开机启动

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.net core 连接 kafka 

有百度到两个比较靠谱的插件Confluent.Kafka和kafka-net-core

参考自 kafka-net-core https://blog.csdn.net/zt102545/article/details/105268492/

生产者

const string topicName = "test";
            var options = new KafkaOptions(new Uri("http://localhost:9092"));

            //创建一个生产者发消息
            using (var producer = new Producer(new BrokerRouter(options)){  BatchSize = 100, BatchDelayTime = TimeSpan.FromMilliseconds(2000) })
            {
                while (true)
                {
                    var message = Console.ReadLine();
                    if (message == "quit") break;

                    if (!string.IsNullOrEmpty(message))
                    {
                        producer.SendMessageAsync(topicName, new[] { new Message(message) });
                    }
                }
            }

消费者

const string topicName = "test";
            var options = new KafkaOptions(new Uri("http://localhost:9092"));


            Task.Run(() =>
            {
                //创建一个消费者
                var consumer = new Consumer(new ConsumerOptions(topicName, new BrokerRouter(options)));
                foreach (var data in consumer.Consume())
                {
                    Console.WriteLine("Response: PartitionId={0},Offset={1} :Value={2}", data.Meta.PartitionId, data.Meta.Offset, data.Value.ToUtf8String());
                }
            });

            Console.ReadLine();

参考自 Confluent.Kafka https://www.cnblogs.com/meowv/p/13614516.html

发布

public async Task PublishAsync<TMessage>(string topicName, TMessage message) where TMessage : class
        {
            var config = new ProducerConfig
            {
                BootstrapServers = "192.168.232.128:9092"
            };
            using var producer = new ProducerBuilder<string, string>(config).Build();
            var sss = await producer.ProduceAsync(topicName, new Message<string, string>
            {
                Key = Guid.NewGuid().ToString(),
                Value = JsonConvert.SerializeObject(message)
            });
        }

订阅

public async Task SubscribeAsync<TMessage>(IEnumerable<string> topics, Action<TMessage> messageFunc, CancellationToken cancellationToken) where TMessage : class
    {
        var config = new ConsumerConfig
        {
            BootstrapServers = "127.0.0.1:9092",
            GroupId = "crow-consumer",
            EnableAutoCommit = false,
            StatisticsIntervalMs = 5000,
            SessionTimeoutMs = 6000,
            AutoOffsetReset = AutoOffsetReset.Earliest,
            EnablePartitionEof = true
        };
        //const int commitPeriod = 5;
        using var consumer = new ConsumerBuilder<Ignore, string>(config)
                             .SetErrorHandler((_, e) =>
                             {
                                 Console.WriteLine($"Error: {e.Reason}");
                             })
                             .SetStatisticsHandler((_, json) =>
                             {
                                 Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} > 消息监听中..");
                             })
                             .SetPartitionsAssignedHandler((c, partitions) =>
                             {
                                 string partitionsStr = string.Join(", ", partitions);
                                 Console.WriteLine($" - 分配的 kafka 分区: {partitionsStr}");
                             })
                             .SetPartitionsRevokedHandler((c, partitions) =>
                             {
                                 string partitionsStr = string.Join(", ", partitions);
                                 Console.WriteLine($" - 回收了 kafka 的分区: {partitionsStr}");
                             })
                             .Build();
        consumer.Subscribe(topics);
        try
        {
            while (true)
            {
                try
                {
                    var consumeResult = consumer.Consume(cancellationToken);
                    Console.WriteLine($"Consumed message '{consumeResult.Message?.Value}' at: '{consumeResult?.TopicPartitionOffset}'.");
                    if (consumeResult.IsPartitionEOF)
                    {
                        Console.WriteLine($" - {DateTime.Now:yyyy-MM-dd HH:mm:ss} 已经到底了：{consumeResult.Topic}, partition {consumeResult.Partition}, offset {consumeResult.Offset}.");
                        continue;
                    }
                    TMessage messageResult = null;
                    try
                    {
                        messageResult = JsonConvert.DeserializeObject<TMessage>(consumeResult.Message.Value);
                    }
                    catch (Exception ex)
                    {
                        var errorMessage = $" - {DateTime.Now:yyyy-MM-dd HH:mm:ss}【Exception 消息反序列化失败，Value：{consumeResult.Message.Value}】 ：{ex.StackTrace?.ToString()}";
                        Console.WriteLine(errorMessage);
                        messageResult = null;
                    }
                    if (messageResult != null/* && consumeResult.Offset % commitPeriod == 0*/)
                    {
                        messageFunc(messageResult);
                        try
                        {
                            consumer.Commit(consumeResult);
                        }
                        catch (KafkaException e)
                        {
                            Console.WriteLine(e.Message);
                        }
                    }
                }
                catch (ConsumeException e)
                {
                    Console.WriteLine($"Consume error: {e.Error.Reason}");
                }
            }
        }
        catch (OperationCanceledException)
        {
            Console.WriteLine("Closing consumer.");
            consumer.Close();
        }
        await Task.CompletedTask;
    }

都亲测有效